Communications Between Volunteers and Health Researchers during Recruitment and Informed Consent: Qualitative Content Analysis of Email Interactions
Bibliographic record
Abstract
BACKGROUND: While use of the Internet is increasingly widespread in research, little is known about the role of routine electronic mail (email) correspondence during recruitment and early volunteer-researcher interactions. To gain insight into the standpoint of volunteers we analyzed email communications in an early rheumatoid arthritis qualitative interview study. OBJECTIVES: The objectives of our study were (1) to understand the perspectives and motivations of individuals who volunteered for an interview study about the experiences of early rheumatoid arthritis, and (2) to investigate the role of emails in volunteer-researcher interactions during recruitment. METHODS: Between December 2007 and December 2008 we recruited 38 individuals with early rheumatoid arthritis through rheumatologist and family physician offices, arthritis Internet sites, and the Arthritis Research Centre of Canada for a (face-to-face) qualitative interview study. Interested individuals were invited to contact us via email or telephone. In this paper, we report on email communications from 12 of 29 volunteers who used email as their primary communication mode. RESULTS: Emails offered insights into the perspective of study volunteers. They provided evidence prospectively about recruitment and informed consent in the context of early rheumatoid arthritis. First, some individuals anticipated that participating would have mutual benefits, for themselves and the research, suggesting a reciprocal quality to volunteering. Second, volunteering for the study was strongly motivated by a need to access health services and was both a help-seeking and self-managing strategy. Third, volunteers expressed ambivalence around participation, such as how far participating would benefit them, versus more general benefits for research. Fourth, practical difficulties of negotiating symptom impact, medical appointments, and research tasks were revealed. We also reflect on how emails documented volunteer-researcher interactions, illustrating typically undocumented researcher work during recruitment. CONCLUSIONS: Emails can be key forms of data. They provide richly contextual prospective records of an underresearched dimension of the research process: routine volunteer-researcher interactions during recruitment. Emails record the context of volunteering, and the motivations and priorities of volunteers. They also highlight the "invisible work" of research workers during what are typically considered to be standard administrative tasks. Further research is needed to fully understand the role of routine emails, what they may reveal about volunteers' decisions to participate, and their implications for research relationships-for example, whether they have the potential to foster rapport, trust, and understanding between volunteer and researcher, and ultimately shift the power dynamic of the volunteer-researcher relationship.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.083 | 0.146 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.009 | 0.013 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".